Posted
by
Unknown Lamer
on Thursday June 26, 2014 @12:20PM
from the didn't-analyze-slashdot dept.

KentuckyFC (1144503) writes The idea that people tend to use positive words more often the negative ones is now known as the Pollyanna hypothesis, after a 1913 novel by Eleanor Porter about a girl who tries to find something to be glad about in every situation. But although widely known, attempts to confirm the hypothesis have all been relatively small studies and so have never been thought conclusive.

Now a group of researchers at Computational Story Lab at the University of Vermont have repeated this work on a corpus of 100,000 words from 24 languages representing different cultures around the world. They first measured the frequency of words in each language and then paid native speakers to rate how they felt about each word on a scale ranging from the most negative or sad to the most positive or happy. The results reveal that all the languages show a clear bias towards positive words with Spanish topping the list, followed by Portuguese and then English. Chinese props up the rankings as the least happy. They go on to use these findings as a 'lens' through which to evaluate how the emotional polarity changes in novels in various languages and have set up a website where anybody can explore novels in this way. The finding that human language has universal positive bias could have a significant impact on the relatively new science of sentiment analysis on social media sites such as Twitter. If there is a strong bias towards positive language in the first place, and this changes from one language to another, then that is obviously an important factor to take into account.